A control valve and its operation is known and need not be described here in detail. A quarter turn valve can be for instance a ball valve or a butterfly valve. Examples of a ball valve are disclosed for instance in U.S. Pat. No. 4,747,578. A control valve is actuated by means of an actuator which moves the stem of the closure member between open and closed positions. An actuator can be operated by means of a cylinder-piston device which in turn is regulated by means of a valve positioner which operates the actuator in response to a control signal.
Control valves are often the most critical components in a control loop.
Control performance of an installed control valve depends primarily on the performance of the control valve but also on process conditions. There are three important factors which have to be taken into account in checking control preformance of an installed valve. They are
Installed flow characteristics and installed gain PA1 Static behaviour of a control valve PA1 Dynamic behaviour of a control valve PA1 Dead band PA1 Hysteresis plus dead band PA1 Repeatability PA1 Conformity/Linearity PA1 Dead time PA1 Time constant(s) PA1 Overshooting PA1 Settling time PA1 Stiction PA1 Lack of control valve maintenance PA1 Poor control valve sizing and selection PA1 Poor tuning of the process controller PA1 Poor process measurements PA1 Big disturbances PA1 providing a simulation model of a process control loop, consisting of a unit process including the flow equations of the valve, a process controller and a process transmitter, to simulate a process with disturbances; PA1 connecting the simulation model to a real control valve, including a valve, an actuator and a positioner; PA1 supplying actuating energy to the positioner; PA1 measuring the valve response; and PA1 determining the process variability during the process. PA1 a control valve, including a valve, an actuator, a positioner and means for supplying actuating energy; PA1 a computer with an I/O card; and PA1 a closed control loop simulator for simulating a unit process, a process controller and a process transmitter.
In analyzing loop performance it must be checked that the valve, actuator and positioner are correctly sized and selected. The best performance is usually achieved by a double acting actuator and a two-stage electropneumatic positioner. Double acting actuators are stiffer than spring return actuators because of the higher actuator pressure level. Therefore, they are less sensitive to disturbances, like dynamic torque or force, and they also give a fast valve response. It is important that the I/P (current to pressure) conversion of an electropneumatic positioner is inside the position feedback loop to compensate the errors by the feedback mechanism.
Control valves are often oversized because all the process data are not available and safety margins are used. If a valve is oversized, only a small part of the control range is in use. Many process controllers still have 10 bit D/A converters, which means about 0.1% resolution for the control signal. The theoretical resolution of input signal is, for example, 0.5% if only one fifth of the full control range is used.
Oversizing means poor control accuracy. For example, if the valve is oversized, then the control valve maximum relative installed gain is about 4 in a typical liquid flow application, and if at the same time, absolute position error in valve travel is 0.5%, then the maximum error in flow is 2.0%.
The control valve installed flow characteristics and gain affect also strongly control valve dynamics and dead time. If the gain varies strongly within the process operating range, also the operating speed of the control loop varies strongly. Control valve oversizing increases control loop dead time. Gain of an oversized valve is high whereby the controller gain must be reduced to prevent control loop instability. This means that the control valve input signal changes coming from process controller are smaller, which leads to strong increase in control valve dead time. This is a significant drawback in process variability.
Static behaviour of a control valve can be described with many different factors, such as
The first two are the most commonly measured nonlinearities of a control valve. They are mainly caused by a backlash and a high actuator load of the valve. Backlash can be removed only by valve maintenance. An actuator load can be decreased by reducing static friction and selecting a large enough actuator.
Repeatability and linearity of a control valve are usually adequate, because control loops are closed by feedback.
Dynamic perfomance of a control valve can be defined, for example, with the following factors
The first four factors can be measured from a step response curve. Results depend a lot on the step size and the valve initial position, because dynamics of a control valve are strongly nonlinear.
Analyzing methods and rules that are based on the linear control theory do not apply well to control valves. A frequency response is rarely used. The methods of frequency analysis are defined mainly for linear systems.
Generally, control valves have to be tested in many operating points.
U.S. Pat. No. 5,249,117 discloses a control system where an estimator is used to generate a simulation of a process according to the information it receives relating to the status of a real process. Other publications relating to valve control systems are U.S. Pat. Nos. 5,109,692 and 5,261,437 and Finnish patent publication 53047. Different methods and systems for estimating process parameters are disclosed in U.S. Pat. Nos. 5,172,312, 4,674,028, 5,195,026, 5,267,139 and 5,357,424.
Process variability represents the quality of the process output of the controlling system. It can be defined in several ways, such as the maximum variability (difference between the maximum value and the minimum value within a certain measurement range); Integrated Error (IE); Integrated Absolute Error (IAE); etc.
The reasons for a high process variability are not easy to find without extra measurements. Poor process control can be caused, for example, by
Process variability is usually measured from sampled process values that are filtered from the real output of a process transmitter.
There are different criteria for analyzing the process variability. The easiest method is to measure the maximum variability of the process output signal. The second way is to calculate the control error area or an area factor between the setpoint and measured variable in a certain time scale. There are many well known integration methods in the control literature, for example ITAE, ITE, ITSE and ISTE. The third way to analyze process variability is to use more complicated signal processing methods.
It is usually difficult to estimate the influence of the control valve performance on the process variability. Flow control and tank level control loops have different sensitivity for control valve nonlinearities. In some cases, dead time is more significant than dead band, and vice versa.
Advances in control algorithms and measurements have been strong and give new possibilities to enhance control valve performance and testing. New smart control valves offer excellent chances to reach higher control performance.